Triple
T949504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanislaus County |
E20487
|
entity |
| Predicate | hasUnincorporatedCommunity |
P6345
|
FINISHED |
| Object |
Grayson
Grayson is an unincorporated community located in Stanislaus County, California.
|
E113939
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Grayson | Statement: [Stanislaus County, hasUnincorporatedCommunity, Grayson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grayson Context triple: [Stanislaus County, hasUnincorporatedCommunity, Grayson]
-
A.
Landry
Landry is a surname most famously associated with Tom Landry, the legendary longtime head coach of the Dallas Cowboys in the National Football League.
-
B.
Winfield
Winfield is a masculine given name most notably borne by 19th-century American military leader Winfield Scott.
-
C.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
D.
Cabell
Cabell is a surname of English origin borne by various notable individuals, including American politician Earle Cabell.
-
E.
Addison
Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Grayson Triple: [Stanislaus County, hasUnincorporatedCommunity, Grayson]
Generated description
Grayson is an unincorporated community located in Stanislaus County, California.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grayson Target entity description: Grayson is an unincorporated community located in Stanislaus County, California.
-
A.
Landry
Landry is a surname most famously associated with Tom Landry, the legendary longtime head coach of the Dallas Cowboys in the National Football League.
-
B.
Winfield
Winfield is a masculine given name most notably borne by 19th-century American military leader Winfield Scott.
-
C.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
D.
Cabell
Cabell is a surname of English origin borne by various notable individuals, including American politician Earle Cabell.
-
E.
Addison
Addison is a small, business-focused town in the Dallas–Fort Worth metropolitan area known for its dense concentration of restaurants, corporate offices, and frequent special events.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3c191ac819099ebf3cb32f096d8 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac119db8c881909cd727b255675c0c |
completed | March 7, 2026, 11:53 a.m. |
| NEDg | Description generation | batch_69ac147efce881909968fbb1c19f0237 |
completed | March 7, 2026, 12:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac14ca3b6c8190955387f5b6003931 |
completed | March 7, 2026, 12:06 p.m. |
Created at: March 1, 2026, 7:40 p.m.